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Blood cell image segmentation based on the Hough transform and fuzzy curve tracing

Authors: Pearl P. Guan; Hong Yan 0001;

Blood cell image segmentation based on the Hough transform and fuzzy curve tracing

Abstract

Segmentation of blood cells is a difficult task because of the presence of noise and the substantial brightness changes within cells in microscopy images. A method based on the Hough transform and fuzzy curve tracing is proposed in this paper. The Hough transform is used to detect the rough circular boundary of each cell. Then, fuzzy curve tracing is employed to detect the exact cell boundary. This approach reduces the effects of noise and the uneven brightness within the cells effectively. In addition, it can even separate slightly overlapping cells. Experiment results show that the proposed method is superior to many existing segmentation methods.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Average
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